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We analyze the role of disease containment policy in the form of treatment in a stochastic economic-epidemiological framework in which the probability of the occurrence of random shocks is state-dependent, namely it is related to the level of disease prevalence. Random shocks are associated with the diffusion of a new strain of the disease which affects both the number of infectives and the growth rate of infection, and the probability of such shocks realization may be either increasing or decreasing in the number of infectives. We determine the optimal policy and the steady state of such a stochastic framework, which is characterized by an invariant measure supported on strictly positive prevalence levels, suggesting that complete eradication is never a possible long run outcome where instead endemicity will prevail. Our results show that: (i) independently of the features of the state-dependent probabilities, treatment allows to shift leftward the support of the invariant measure; and (ii) the features of the state-dependent probabilities affect the shape and spread of the distribution of disease prevalence over its support, allowing for a steady state outcome characterized by a distribution alternatively highly concentrated over low prevalence levels or more spread out over a larger range of prevalence (possibly higher) levels.

Using a one-sector, discrete-time Ramsey model, we analyze and compare the implications for welfare, capital accumulation, and speed of convergence to the steady state of two classes of utility functions that represent Gorman preferences, namely homothetic and Stone–Geary preferences. For identical economies, we show that the preference structure does not affect only the capital dynamics and social welfare but also the speed of convergence to the steady-state equilibrium.

We analyze the effectiveness of environmental policy in a framework in which households’ utility is determined by both private and social components, representing their extrinsic and intrinsic motivations to undertake green actions, respectively. Environmental policy, in the form of a subsidy aiming to incentivize the adoption of a green technology, on the one hand, directly increases households’ extrinsic motivation, while, on the other hand, indirectly decreases their intrinsic motivation. We show that, provided that the indirect effect dominates, the policy leads to crowding‐out of intrinsic motivation which ultimately undermines the effectiveness of the policy itself. Specifically, despite its positive effect on environmental outcomes in the short run, the policy will lead to a deterioration in long‐run environmental outcomes, giving rise to a reverse green‐paradox‐like outcome. Moreover, even in the case in which the direct effect dominates, provided that the indirect effect is large enough, the policy will generate a deterioration in short‐run environmental outcomes. These results clearly suggest that the optimal design of environmental policy is particularly complicated since it requires to take into account also its effects on intrinsic motivation.

We analyze a macroeconomic model with intergenerational equity considerations and spatial spillovers, which gives rise to a multicriteria optimization problem. Intergenerational equity requires to add in the definition of social welfare a long run sustainability criterion to the traditional discounted utilitarian criterion. The spatial structure allows for the possibility of heterogeneiity and spatial diffusion implies that all locations within the spatial domain are interconnected via spatial spillovers. We rely on different techniques (scalarization, $$\epsilon $$ -constraint method and goal programming) to analyze such a spatial multicriteria problem, relying on numerical approaches to illustrate the nature of the trade-off between the discounted utilitarian and the sustainability criteria.

We analyze a transboundary pollution control problem in a heterogeneous two-country differential game setting in which regulators care for the implications of environmental policies on the competitiveness. We characterize the noncooperative and the cooperative solutions, showing that under both scenarios, in the presence of competitiveness considerations, heterogeneous countries will generally set different carbon taxes. This suggests, while implementing a mitigation policy is necessary to combat climate change, a universally homogeneous policy may not be optimal. Moreover, when countries are symmetric, except for their degree of competitiveness concerns, under noncooperation introduction of such concerns lowers the abatement policies in both countries, however, the self-effect is stronger than the cross-effect. Nevertheless, under cooperation, an increase in country j’s competitiveness concerns leads to more stringent policies in country i, while, the self-effect could be either positive or negative. The latter result emphasizes the importance of cooperation to tackle pollution in the presence of competitiveness concerns.

We provide a simple micro-foundation of the tourism area life cycle hypothesis, based on tourists’ utility maximization. As a result of social interactions among tourists which determine destinations popularity, the market share of visitors which decides to visit a specific destination follows a logistic dynamics, consistent with what predicted by the tourism area life cycle hypothesis. We show that different preference drivers explain the duration of the different tourism area life cycle stages: the net benefit from visiting the destination characterizes the exploration, involvement, and development phases, while social effects associated with destination popularity characterize the phases of consolidation and stagnation Different from previous studies our results hold true independently of whether we focus on the repeating or non-repeating segment of the tourism market. We also provide a calibration of our model to the case of the city of Venice (Italy) showing that it performs well in capturing the evolution of tourism in the historical center of the city over the last 60 years, suggesting that TALC-like dynamics may occur even in the context of cultural and heritage destinations.

We develop an epidemiological approach to analyze how financial contagion may affect and be affected by economic activity. We show that, according to specific parameter values, the economy may converge either to a non-speculative or to a speculative equilibrium: in the former situation the level of per capita income is maximal, while in the latter it is reduced by financial contagion. The presence of economic and financial feedback effects may also give rise to macroeconomic fluctuations during the transitional path, clearly showing that such economic and financial links are an important driver of the short run macroeconomic performance. By extending the analysis to a spatial dimension, we also show that financial contagion in some specific region may propagate quickly also in regions far away from those in which the contagion initially occurs, highlighting the role of regional policy coordination to avoid interregional contagion.

We develop a multicriteria approach, based on both scalarization and goal programming techniques, in order to analyze the trade off between economic growth and environmental outcomes in a framework in which the economy and environment relation is bidirectional. On the one hand, economic growth by stimulating production activities gives rise to emissions of pollutants which deteriorate the environment. On the other hand, the environment affects economic activities since pollution generates a production externality determining how much output the economy can produce and reducing welfare. In this setting we show that optimality dictates an initial overshooting followed by economic degrowth and rising pollution. This implies that independently of the relative importance of economic and environmental factors, it is paradoxically optimal for the economy to asymptotically reach the maximum pollution level that the environment is able to bear.

We develop an analytically tractable population dynamics model of heterogeneous agents to characterize how social interactions within a neighborhood determine the dynamic evolution of its ethnic composition. We characterize the conditions under which integration or segregation will occur, which depends on the majority’s social externality parameter and net benefit from leaving, and the minority’s leaving probability. Minority segregation may result from the process of tipping, which may arise from three possible channels: two are related to exogenous shocks (migration flows and changes in tipping points) and one is related to the endogenous probabilistic features of our framework (endogenous polarization). This characterization of integration and segregation conditions yields interesting policy implications for social and urban planning policies to mitigate segregation.

The COVID-19 pandemic is still ravaging the planet, but its (short-, medium-, and long-term) diverse effects on health, economy, and society are far from being understood. This article investigates the potential impact of a deadly epidemic and its main nonpharmaceutical control interventions (social distancing vs. testing–tracing–isolation, TTI) on capital accumulation and economic development at different time scales. This is done by integrating an epidemiological susceptible–infectious–recovered model with a Solow-type growth model including public expenditure, as a parsimonious setting to offer insights on the trade-off between protecting human lives and the economy and society. The work clarifies (i) the long-term interactions amongst a deadly infection, demography, and capital accumulation, (ii) the lack of viability of persistent social distancing measures also using an analytical characterization, and the threat of policy-enhanced COVID-19 endemicity, (iii) the potentially high return on investments in TTI activities to avoid future lockdowns and related capital disruption. It also quantifies the welfare effects of a range of policies, confirming a counterintuitive role for tax-funded preventive investments aimed at strengthening TTI as more desirable interventions than generalized lockdowns. © 2021 The Authors. Journal of Public Economic Theory published by Wiley Periodicals LLC.

We analyze a two-sector stochastic economic growth model of green transition with pollution externalities and foreign capital. The final good is produced by combining dirty and clean inputs, with different implications on pollution accumulation. Pollution negatively affects production capabilities and can be reduced by switching to the clean input. The clean input is produced by using the dirty input and the foreign capital received (in the form of dirty input). Random shocks make the effective economy’s ability to transition to green activities highly uncertain, eventually undermining its economic development. Such a setting gives rise to a dynamic system represented by a three dimensional affine iterated function system. We show that the economy’s steady state is represented by an invariant measure supported on a compact set, characterizing its fractal nature and showing that its attractor may be a distorted Sierpinski tetrahedron.

We analyze a purely dynamic model of public debt stabilization under ambiguity. We assume that the debt to GDP ratio is described by a random variable, and thus it can be characterized by investigating the evolution of its density function through iteration function systems on mappings. Ambiguity is associated with parameter uncertainty which requires policymakers to respond to such an additional layer of uncertainty according to their ambiguity attitude. We describe ambiguity attitude through a simple heuristic rule in which policymakers adjust the available vague information (captured by the empirical distribution of the debt ratio) with a measure of their ignorance (captured by the uniform distribution). We show that such a model generates fractal-type objects that can be characterized as fixed-point solutions of iterated function systems on mappings. Ambiguity is a source of unpredictability in the long run outcome since it introduces some singularity features in the steady state distribution of the debt ratio. However, the presence of some ambiguity aversion removes such unpredictability by smoothing out the singularities in the steady state distribution.

We analyze the optimal debt reduction problem in an uncertainty context. The social planner has a finite horizon and seeks to minimize the social costs associated with debt repayment by taking into account not only the short-run costs of the policy, but also the long-run costs associated with the outstanding level of debt. We characterize the optimal policy and the dynamics of the debt-to-GDP ratio, showing that it will decrease over time if economic policy is effective enough. We characterize how the evolution of the debt-to-GDP ratio depends on the main parameters and we present a simple calibration based on Greek data to illustrate the implications of our analysis in real-world setups.

We explore the relationship between tourism specialization and structural change in an endogenous growth model, analyzing its implications for both economic growth and tourist flows. We consider a two-sector economic growth model where the development of tourism activities generates a production externality and a structural change, which modifies the resources-use intensity, ultimately affecting tourist flows. We characterize the balanced growth path equilibrium and analyze under which conditions structural change may generate fast economic growth, providing a theoretical support for the empirical evidence on tourism countries. We also show that structural change may alternatively lead to stages of rejuvenation, stagnation, or decline consistently with what advanced by the tourism area life cycle hypothesis. By combining these different results, we also show that an eventual phase of decline generated by structural change does not necessarily have to be interpreted as a poor economic outcome since there might exist a bell-shaped relationship between residents’ income and number of visitors.

We analyze the simplest possible model of endogenous growth to account for the role of financial development. In our setting, financial development affects productivity and determines the amount of resources subtracted to capital investment. We show that under very general assumptions, the relation between economic growth and financial depth is nonmonotonic, and eventually bell-shaped. We empirically assess our results in a framework that allows to distinguish between long-run and short-run effects. We establish a cointegrating relation and derive the long-run elasticities of per capita gross domestic product (GDP) with respect to employment, the physical capital stock, and financial depth–relying on linear as well as nonlinear models for the finance-growth nexus. We employ the results of the first step estimation to specify an error–correction model and find that there is strong evidence for a nonlinear relationship between financial depth and per capita GDP, consistently with what was predicted by our theoretical model.

Racial segregation is a salient feature of cities in the United States. Models like Schelling (1971) show that segregation can arise through white preferences for residing near minorities. Once the threshold or “tipping point” is passed, the models predict that all whites will leave. Our paper uses census-tract data for six cities in the United States from the 1930s and 1970–2010 to measure decadal, city-specific tipping points. We use a structural break procedure to estimate the tipping points and incorporate these in a regression-discontinuity design to estimate the impact on population trends for neighborhoods that exceed that threshold while controlling for city-specific trends in migration. We find that the magnitude of white flight for neighborhoods that have tipped in 2000 has fallen to between 23% and 36% of the level seen in 1970. There was no discontinuity in white flight after accounting for migration trends during the Great Depression. Finally, we show that in-migration of minorities in tipped neighborhoods do not fill in the gap left by white flight.

We analyze a multi-sector growth model subject to random shocks affecting the two sector-specific production functions twofold: the evolution of both productivity and factor shares is the result of such exogenous shocks. We determine the optimal dynamics via Euler–Lagrange equations, and show how these dynamics can be described in terms of an iterated function system with probability. We also provide conditions that imply the singularity of the invariant measure associated with the fractal attractor. Numerical examples show how specific parameter configurations might generate distorted copies of the Barnsley’s fern attractor.

We analyze the implications of endogenous fertility choices on both economic and environmental performances in a stylized AK-type growth model. Differently from what traditionally assumed in the growth and environment literature, we allow pollution to be not only a by-product of productive activities by firms but also a result of households’ behavior, as suggested by the celebrated IPAT equation. We show that along the balanced growth path equilibrium, economic growth may be non-monotonically related to the population growth rate as agents care for the environment; moreover, demographic policies can be used both to achieve win-win outcomes (simultaneously fostering economic growth and improving environmental quality) and to stabilize the otherwise non-monotonic economic and population growth relationship.

We analyze the impact of financial development on economic growth. Differently from previous studies that focus mainly on balanced growth path outcomes, we also analyze the transitional dynamics of our model economy by using a finance‐extended Uzawa–Lucas framework where financial intermediation affects both human and physical capital accumulation. We show that, under certain rather general conditions, economic growth may turn out to be non‐monotonically related to financial development (as suggested by the most recent empirical evidence) and that too much finance may be detrimental to growth. We also show that the degree of financial development may affect the speed of convergence, which suggests that finance may play a crucial role in determining the length of the recovery process associated with exogenous shocks. Moreover, in a special case of the model, we observe that, under a realistic set of parameters, social welfare decreases with financial development, meaning that even when finance positively affects economic growth the short‐term costs associated with financial activities more than compensate their long‐run benefits.

We analyze a transboundary pollution control problem in a heterogeneous two-country differential game in which each country’s regulator cares for the implications of environmental policy on its competitiveness. We characterize and compare the noncooperative and the cooperative solutions, showing that under both scenarios, the heterogeneous countries impose different tax rates despite such competitiveness concerns. This may suggest that, while implementing some kind of mitigation policy is necessary to combat climate change, a universally homogeneous environmental tax may not be either desirable or optimal.

We present an alternative to the geometric Brownian motion in order to model random shocks in economics, by focusing on the stochastic logistic process, which is a natural generalization of the geometric Brownian motion. We describe some potential applications in the context of economic growth, and show that its degree of tractability is very similar to that of the geometric Brownian motion, and thus its use can effectively improve the limits (related to the presence of a constant drift) of the geometric Brownian motion to model uncertainty.

We analyze a simple stochastic model of economic growth in which physical and health capital accumulation jointly contribute to determine long run economic growth. Health capital is subject to random shocks via the effects of behavioral changes: unpredictable changes in individuals’ attitude toward healthy behaviors may reduce the effectiveness of health services provision; this in turn, by reducing the production of new health capital, lowers economic production activities negatively affecting economic growth. Unlike the extant literature, we assume that the probability with which such random shocks occur is not constant but state-dependent. Specifically, the probability that behavioral changes will negatively impact on health capital and economic growth depends on the level of economic development, proxied by the relative abundance of health capital with respect to physical capital. We show that our model’s dynamics can be converted into an iterated function system with state-dependent probabilities which converges to an invariant self-similar measure supported on a (possibly fractal) compact attractor. We develop a numerical method to approximate the invariant distribution to illustrate its features in specific model’s parametrizations, exemplifying thus the effects of state-dependent probabilities on the model’s steady state.

We show that, even in a framework in which monopolistic exploitation of patents does not occur, patents still give rise to serious drawbacks. We rely on a recombinant growth framework that provides a stylized but clear description of the formation of knowledge externalities. In our setting a benevolent government buys immediately new patents in a competitive market and releases their contents for free. We show that inefficiencies nevertheless arise and welfare can be improved by correcting the market price through a tax–subsidy scheme. We characterize the (asymptotic) steady-state equilibrium, and some properties of the transitional path. We show that if certain conditions are met, then the economy will converge to its (asymptotic) balanced growth path, and along such a pathgrowth will be independent of the policy parameter; conversely, transition dynamics are affected by the choice of the policy parameter. We then quantitatively analyze the effect of different policy interventions on welfare, and show that stricter tax (weaker appropriability) regimes lead to higher social welfare.

We analyze the spatio-temporal dynamics of a simple model of macroeconomic geography in which demography and pollution dynamics mutually affect each other. Pollution, by reducing the carrying capacity of the natural environment – which determines the maximum amount of people a given location can effectively bear – crucially affects labor force dynamics which in turn alter the amount of resources available for abatement activities aiming to reduce pollution. Such mutual links determine the eventual sustainability of the development process in different locations and economies, and spatial interactions further complicate the picture. We show that neglecting the existence of mutual feedback between population and pollution leads to misleading conclusions about the eventual sustainability of a specific location. We also show that even neglecting the existence of spatial externalities can lead to misleading conclusions about the sustainability of different regions in the spatial economy. This suggests thus that both the nature of the population and pollution relationship and geographical factors may play a critical role in the process of sustainable development.

We analyze the determination of the optimal intensity and duration of social distancing policy aiming to control the spread of an infectious disease in a simple macroeconomic–epidemiological model. In our setting the social planner wishes to minimize the social costs associated with the levels of disease prevalence and output lost due to social distancing, both during and at the end of epidemic management program. Indeed, by limiting individuals’ ability to freely move or interact with others (since requiring to wear face mask or to maintain physical distance from others, or even forcing some businesses to remain closed), social distancing has on the one hand the effect to reduce the disease incidence and on the other hand to reduce the economy’s productive capacity. We analyze both the early and the advanced epidemic stage intervention strategies highlighting their implications for short and long run health and macroeconomic outcomes. We show that both the intensity and the duration of the optimal social distancing policy may largely vary according to the epidemiological characteristics of specific diseases, and that the balancing of the health benefits and economic costs associated with social distancing may require to accept the disease to reach an endemic state. Focusing in particular on COVID-19 we present a calibration based on Italian data showing how the optimal social distancing policy may vary if implemented at national or at regional level.

We analyze a simple endogenous growth model with environmental interactions. Economic production generates emissions of pollutants whose environmental impact is mitigated by abatement activities financed by government expenditure; environmental quality affects preferences but does not play any productive role. We show that government intervention, by reallocating resources from capital accumulation to environmental preservation activities, allows the economy to achieve a sustainable balanced growth path. Along such a path, softer environmental policy regimes lead to win–win outcomes, fostering economic growth and improving environmental quality. Such a result needs to be interpreted as a long run outcome, but it clearly shows that the compatibility between economic growth and environmental improvement is far from automatic. Indeed, in the long run it could paradoxically be the case that both the economy and the environment benefit from low levels of environmental protection.

Can success in sport events be a positive determinant of the number of tourists arriving in a country where successful teams are based? In order to test this hypothesis, this paper focuses on football events linking national teams' outstanding performance in the FIFA World Cup tournaments to tourist inflows at the national level. By applying panel cointegrating regressions, the paper finds that countries whose national teams obtain surprising results (e.g. Costa Rica in 2014) in the World Cup final tournaments benefit from a significant increase in tourist arrivals after two years. In countries whose national teams qualify as football champions, the benefits appear in the first and second years following the event and the result is stronger. This suggests that outstanding performance in sport events can favor tourism and economic development in successful teams’ home countries. Policies aiming to promote national sporting teams can thus have significant effects on other sectors of the economy., Highlights • Tests the relationship between performance of national soccer team and tourist arrivals. • Uses data from 1995 to 2017 for 11 surprise teams and five champion teams. • Considers the FIFA World Cups of 1998, 2002, 2006, 2010 and 2014. • Applies panel cointegrating regressions. • Outstanding performance in the World Cups increases tourist arrivals one to two years after these events.

We analyze the implications of innovation and social interactions on economic growth in a stylized endogenous growth model with heterogeneous research firms. A large number of research firms decide whether to innovate or not, by taking into account what competitors (i.e., other firms) do. This is due to the fact that their profits partly depend on an externality related to the share of firms which actively engage in research activities. Such a share of innovative firms also determines the evolution of technology in the macroeconomy, which ultimately drives economic growth. We show that when the externality effect is strong enough multiple BGP equilibria may exist. In such a framework, the economy may face a low growth trap suggesting that it may end up in a situation of slow long-run growth; however, such an outcome may be fully solved by government intervention. We also show that whenever multiple BGP exist, they are metastable meaning that the economy may cyclically fluctuate between the low and high BGP as a result of shocks affecting the individual behavior of research firms.

We analyze the spatio-temporal dynamics of a simple model of economic geography in which population and pollution dynamics are mutually interdependent. Pollution by reducing the carrying capacity of the natural environment, which determines the maximum amount of people a given location can effectively bear, affects labor force dynamics which in turn alter pollution emissions. Such mutual links determine the development path followed by different locations, and spatial interactions further complicate the picture. We show that neglecting the existence of spatial externalities can lead to misleading predictions about the development path followed by different locations in the spatial economy.

We analyze the effect of uncertainty on economic growth and environmental quality in a concave stochastic bicriteria dynamic problem, solved by means of scalarization techniques and the Hamilton–Jacobi–Bellman equation. Specifically, we focus on an endogenous growth model with purposive abatement activities, where environmental quality, subject to random shocks, is merely a source of utility and does not play any productive role. We show that even in the absence of direct (environmental) productivity effects, along the optimal path production results enhanced by an indirect productivity effect, which transforms environmental quality into the engine of growth. However, this does not prevent uncertainty to dampen economic and environmental performance, leading to a lower social welfare than in a deterministic framework.

We provide a very simple macroeconomic investigation of the role that structural changes might play in generating inverted U-shaped income–pollution relationships. Differently from previous research which mainly focuses on empirical, static or general equilibrium models, we develop a standard balanced growth path (BGP) analysis. We show that along the BGP equilibrium an inverted U-shaped income–pollution relationship may occur as a response to structural changes, but whether this is the case or not it will crucially depend upon the magnitude of a production externality parameter. Moreover, we show that the negative relationship between income and pollution can only be a transitory phenomenon, and in the long run pollution will increase as income rises, generating overall an N-shaped pattern.